The effects of method of generating circular slip surfaces on determining the critical slip surface by particle swarm optimization

Kalatehjari, Roohollah; Ali, Nazri; Kholghifard, Mehrdad; Hajihassani, Mohsen

doi:10.1007/s12517-013-0922-5

Cited by 42 publications

(19 citation statements)

References 28 publications

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“…In 2D analysis, it can be employed to determine the shape of the CSS in a predefined 2D section of the slope. Different shapes are possible for slip surfaces in 2D analysis, such as circular, ellipse, spiral, and polygonal or arbitrary surfaces [ 22 , 41 , 42 ]. In contrast, 3D slip surfaces such as spherical, ellipsoidal, and Nonuniform Rational B-Splines (NURBS) are commonly assumed in 3D analysis [ 23 , 43 , 43 , 44 ].…”

Section: Application Of Pso In Slope Stability Analysismentioning

confidence: 99%

“…Furthermore, in a comparison with pattern method, they [ 17 ] reported that PSO is capable of finding the global minimum FOS and its related CSS in different slopes. Ever since, PSO has been used progressively as an effective technique to deal with the problem of determining the CSS, to name a few, Cheng et al [ 17 ], Cheng et al [ 18 ], Zhao et al [ 19 ], Tian et al [ 20 ], Li et al [ 21 ], Kalatehjari et al [ 22 , 23 ], and W. Chen and P. Chen [ 24 ]. However, the contribution of PSO was limited to 2D slope stability problem.…”

Section: Introductionmentioning

confidence: 99%

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The Contribution of Particle Swarm Optimization to Three-Dimensional Slope Stability Analysis

Kalatehjari

Rashid

Ali

et al. 2014

The Scientific World Journal

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Over the last few years, particle swarm optimization (PSO) has been extensively applied in various geotechnical engineering including slope stability analysis. However, this contribution was limited to two-dimensional (2D) slope stability analysis. This paper applied PSO in three-dimensional (3D) slope stability problem to determine the critical slip surface (CSS) of soil slopes. A detailed description of adopted PSO was presented to provide a good basis for more contribution of this technique to the field of 3D slope stability problems. A general rotating ellipsoid shape was introduced as the specific particle for 3D slope stability analysis. A detailed sensitivity analysis was designed and performed to find the optimum values of parameters of PSO. Example problems were used to evaluate the applicability of PSO in determining the CSS of 3D slopes. The first example presented a comparison between the results of PSO and PLAXI-3D finite element software and the second example compared the ability of PSO to determine the CSS of 3D slopes with other optimization methods from the literature. The results demonstrated the efficiency and effectiveness of PSO in determining the CSS of 3D soil slopes.

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Section: Application Of Pso In Slope Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Contribution of Particle Swarm Optimization to Three-Dimensional Slope Stability Analysis

Kalatehjari

Rashid

Ali

et al. 2014

The Scientific World Journal

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“…There are some good optimization algorithms that are usually employed in solving geotechnical engineering problems such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Firefly Algorithm (FA), and Artificial Bee Colony (ABC). Out of these algorithms, the PSO is one of the most popular optimization techniques that has been mostly used in geotechnical engineering including slope stability and foundation engineering [27,[34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Soft Computing Model Using Random Forest and Particle Swarm Optimization for Estimation of Undrained Shear Strength of Soil

Pham

et al. 2020

Sustainability

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Determination of shear strength of soil is very important in civil engineering for foundation design, earth and rock fill dam design, highway and airfield design, stability of slopes and cuts, and in the design of coastal structures. In this study, a novel hybrid soft computing model (RF-PSO) of random forest (RF) and particle swarm optimization (PSO) was developed and used to estimate the undrained shear strength of soil based on the clay content (%), moisture content (%), specific gravity (%), void ratio (%), liquid limit (%), and plastic limit (%). In this study, the experimental results of 127 soil samples from national highway project Hai Phong-Thai Binh of Vietnam were used to generate datasets for training and validating models. Pearson correlation coefficient (R) method was used to evaluate and compare performance of the proposed model with single RF model. The results show that the proposed hybrid model (RF-PSO) achieved a high accuracy performance (R = 0.89) in the prediction of shear strength of soil. Validation of the models also indicated that RF-PSO model (R = 0.89 and Root Mean Square Error (RMSE) = 0.453) is superior to the single RF model without optimization (R = 0.87 and RMSE = 0.48). Thus, the proposed hybrid model (RF-PSO) can be used for accurate estimation of shear strength which can be used for the suitable designing of civil engineering structures.

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“…To guarantee the stability of a homogenous slope, the circular arc method is traditionally used for stability analysis. The two main objectives of slope stability analysis are calculating FOS for a given slip surface and determining the CSS for a given slope [ 3 ]. The Swedish circle method, the so-called Fellenius slice method, is a widely used classic algorithm for calculating the FOS of an arc sliding slope [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Numerical Computation of Homogeneous Slope Stability

Xiao

Ke-min

Ding

et al. 2015

Computational Intelligence and Neuroscience

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To simplify the computational process of homogeneous slope stability, improve computational accuracy, and find multiple potential slip surfaces of a complex geometric slope, this study utilized the limit equilibrium method to derive expression equations of overall and partial factors of safety. This study transformed the solution of the minimum factor of safety (FOS) to solving of a constrained nonlinear programming problem and applied an exhaustive method (EM) and particle swarm optimization algorithm (PSO) to this problem. In simple slope examples, the computational results using an EM and PSO were close to those obtained using other methods. Compared to the EM, the PSO had a small computation error and a significantly shorter computation time. As a result, the PSO could precisely calculate the slope FOS with high efficiency. The example of the multistage slope analysis indicated that this slope had two potential slip surfaces. The factors of safety were 1.1182 and 1.1560, respectively. The differences between these and the minimum FOS (1.0759) were small, but the positions of the slip surfaces were completely different than the critical slip surface (CSS).

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The effects of method of generating circular slip surfaces on determining the critical slip surface by particle swarm optimization

Cited by 42 publications

References 28 publications

The Contribution of Particle Swarm Optimization to Three-Dimensional Slope Stability Analysis

The Contribution of Particle Swarm Optimization to Three-Dimensional Slope Stability Analysis

A Novel Hybrid Soft Computing Model Using Random Forest and Particle Swarm Optimization for Estimation of Undrained Shear Strength of Soil

Numerical Computation of Homogeneous Slope Stability

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